SINGLE TABLE HASH CLUSTERS DEMYSTIFIED

In this post, I will discuss single table hash clusters which we can fetch a row requiring only a single block get most of the time. Hash clusters are quite similar toindex clusters, except that the cluster index is missing. The data in the cluster itself acts like an index.

First, let us see how is the data stored in a hash cluster.

Let’s say we have a hash cluster table with two columns id (number) and text (char) where id is the key column. On inserting a record with id = 1 into the table- The key column value (1 here) is hashed and converted into a diskaddress.- The record is placed at the disk address returned above.Now, if another record is inserted with id = 2, , the key column value 2 is hashed to return a different address. Thus records having different key values will be placed at different disk addresses whereas all the records with same key value will go to the same address on the disk.

Now, let’s see how the data is retrieved from a hash cluster as compared to a conventional indexed cluster table.In a conventional indexed heap table , if there is a unique index on the column being queried, the algorithm followed is :- Perform unique scan of the index to locate the key and get the rowid (i.e. at least 2 I/O’s – one for index root block, one for index leaf block and may be more as blevel of the index increases)

– Using the rowid obtained above, access the table by rowid (i.e. one I/O to get the data)

Hash clusters having composite cluster keys or cluster keys made up of non integer columns use the internal hash function.

If a non-integer cluster key value is supplied and internal hash function is bypassed , the operation (INSERT or UPDATE statement) is rolled back and an error is returned.

SIZE <size_number>

Specifies the amount of space in bytes reserved in a block to store all rows having the same cluster key value or the same hash value. This space decides the maximum number of cluster or hash values stored in a data block.

SINGLE TABLE

SINGLE TABLE indicates that this hash cluster can contain only one
table.. However, you may drop the table and create another table in the
same cluster.

HASHKEYS <hash_keys_number>

Specify the HASHKEYS clause to create a hash cluster and specify the number of hash values for the hash cluster.The HASHKEYS value specifies and limits the number of unique hash values that can be generated by the hash function used by the cluster. (how many distinct values you anticipate for the cluster key over time)Oracle Database rounds up the HASHKEYS value to the nearest prime number to obtain the actual number of hash values. The minimum value for this parameter
is 2. If you omit the HASHKEYS parameter, the database creates an indexed cluster by default.

When you create a hash cluster, the database immediately allocates space for the cluster based on the values of the SIZE and HASHKEYS parameters.

It allocates a hash table to hold HASHKEY number of cluster keys of SIZE bytes each.

HASH IS <expr>

Specify an expression to be used as the hash function for the hash cluster. Must evaluate to a positive value

If you omit the HASH IS clause, then Oracle Database uses an internal hash function for the hash cluster.

—- Overview –

– create two single table hash clusters with
size = 8k , hashkeys = 4

cluster HSH_CLUSTER_ROWSIZ_8K and HSH_CLUSTER_ROWSIZ_4K

— Create table hash_cluster_tab_ROWSIZE_8k in cluster HSH_CLUSTER_ROWSIZ_8K with row size such that only one record fits one block

— Create table hash_cluster_tab_ROWSIZE_4k in cluster HSH_CLUSTER_ROWSIZ_4K with row size such that two records fit one block

— insert records for 5 distinct key values to both the tables

— Each record goes to a different block as hashkeys has been set to 5 (next prime no.) and each block can have records with only one hash key.

— Try to access record with a key value – single I/O

— Insert records for 6th key values although provision has made for 5 keys only and check that hash collision takes place as id = 6 is mapped to one of the already existing hash values (id=1)

— Add another record for id = 1 and check that multiple blocks containing rows with same hash value are chained together.

— Check that each block contains records for a maximum of 3 hashkeys.
— Insert 3 records with id = 1 in all the 3 tables

— Add records for id’s = 6 to 9 i.e. four keys more than what we have defined the cluster for (5).

— Note that it takes time to add these records

— Check that there is collision for hash keys – Multiple key values correspond to the same hash key – the hash chain for a hash key becomes longer and contains records with different key values.

— Check that overallocation takes place i.e. a block holds rows for hashkeys more than it is expected to hold (3).– Implementation –

– create two single table hash clusters with
size = 8k , hashkeys = 4

cluster HSH_CLUSTER_ROWSIZ_8K and HSH_CLUSTER_ROWSIZ_4K

– The cluster key column for the clusters is id. The column in table in this cluster does not have to be called ID, but it must be NUMBER(2), to match this definition.

– Also we have specified a SIZE 8K option which means that we expect about 8K bytes of data to be associated with each cluster key value. Oracle will use it to compute the maximum number of cluster keys that could fit per block. Here, maximum no. of hash keys per block = Block size/SIZE = 8K/8K = 1 i.e. each block can contain records having only one hash key.

– The value of HASHKEYS limits the number of unique hash values that can be generated by the hash function used for the cluster. Oracle rounds the number you specify for HASHKEYS to the nearest prime number (5 here as we have set HASHKEYS to 4 and 5 is the next prime number) i.e. for any cluster key value, the hash function generates a maximum of 5 values.

– In hash_cluster_tab_rowsize_4k, id = 6 is hashed
to one of the existing hash values and record is placed in the same block (138)
as the earlier containing record with same hash key as two records can fit one
block. Hence block 138 becomes overflow block as it contains more hashvalues
than it is configured for.

Here id = 6 has been mappped to same hash
value as id = 1 and has occupied the same block as id = 1

– In hash_cluster_tab_rowsize_8k, since one row can
fit one block, Newly added rows have gone to a new block (147) as
the earlier blocks can’t accommodate new rows.

But it has again been mapped to one of the
already existing hash values and is chained to the blocks containing those key
values.

In hash_cluster_tab_rowsize_2k, although we have space for another row
in blocks containing id = 2,3,4,5 , the new record goes to a new block(142) as
one block can contain only one hashvalue. From now onwards, a block which
contains id = 1 may also contain an entry for id=6 and vice versa since both of
them hash to the same value.

In hash_cluster_tab_rowsize_8k also , the new record goes to a new
block (135) as a block can contain only one row. Presuming that id = 6 and 1
hash to the same value, blocks containing id = 1 (130 and 135) have been
chained to block containing id=6 (135).

From now onwards, when we search for id =1 or id = 6 we will have to scan a
larger no. of blocks.Hence, if actual no. of cluster keys exceeds the specified
value for HASHKEYS, the likelihood of a collision (two cluster
key values having the same hash value) increases and performance degrades.

Therefore, the distribution of rows in a hash cluster is directly
controlled by the value set for the HASHKEYS parameter. With a larger number of
hash keys for a given number of rows, the likelihood of
a collision (two cluster key values having the same hash value)
decreases. Minimizing the number of collisions is important because overflow
blocks (thus extra I/O) might be necessary to store rows with hash values that
collide.

Now let’s play around with SIZE clause...

The maximum number of hash keys assigned per data block is determined by the
SIZE parameter of the CREATE CLUSTER command. SIZE is an estimate of the total
amount of space in bytes required to store the average number of rows associated
with each hash value. For example, if the available free space per data block
is 1700 bytes and SIZE is set to 500 bytes, three hash keys (round(1700/500))
are assigned per data block.

Note: The importance of the SIZE parameter of hash clusters is analogous
to that of the SIZE parameter for index clusters. However, with index clusters,
SIZE applies to rows with the same cluster key value instead of the same hash
value.

Although the maximum number of hash key values per data block is determined
by SIZE, Oracle does not actually reserve space for each hash key value in the
block. For example, if SIZE determines that three hash key values are allowed
per block, this does not prevent rows for one hash key value from taking up all
of the available space in the block. If there are more rows for a given hash
key value than can fit in a single block, the block is chained, as necessary.

Since 8 rows can fit one block, all the 3 rows inserted go to
block 161

Now block 161 has 6 rows

i.e. although the maximum number of hash key values per data
block as determined by SIZE is 3, Oracle does not actually reserve space for
each hash key value in the block. Rows for one hash key value(id=1) can take up
all of the available space in the block.

– For row size = 2K

3 rows can fit one block

Block 169 containing id=1 already has 3 rows

Although 1 more row can fit in block 170 , newly added
rows for id=1 go to anothet block 172

i.e. when key value is inserted for the first time, its
blockmate keys are decided or let’s say that it is decided
records for which hash values will stay together. From then onwards, records
for its blockmate keys will always reside on the same block. Hence, once hash
values occupying a block have been grouped (1,2,5 and 3,4) further records will
occupy only the blocks along with their blockmates.

You can also specify any SQL expression as the hash function for a hash
cluster. If your cluster key values are not evenly distributed among the
cluster, you should consider creating your own hash function that more
efficiently distributes cluster rows among the hash values.

For example, if you have a hash cluster containing employee information and
the cluster key is the employee’s home area code, it is likely that many
employees will hash to the same hash value. To alleviate this problem, you can
place the following expression in the HASH IS clause of the CREATE CLUSTER
command:

MOD((emp.home_area_code + emp.home_prefix + emp.home_suffix), 101)

The expression takes the area code column and adds the phone prefix and
suffix columns, divides by the number of hash values (in this case 101), and
then uses the remainder as the hash value. The result is cluster rows more
evenly distributed among the various hash values.

CREATE CLUSTER address

(postal_code NUMBER, country_id CHAR(2))

HASHKEYS 20

HASH IS MOD(postal_code + country_id, 101);

Summary:

— Hash Cluster tables are appropriate for data that is read frequently via
an equality comparison on the key. If an index scan is used for a key
value, as more no. of users search for the same record, they hit the same index
block which becomes the “hot block” leading to more contention for
the cache buffers chains (cbc) latch. Replacing indexed tables with hash cluster
tables in this case can resolve the problem of contention for CBC latches.

— you cannot range scan a table in a hash cluster without adding a
conventional index to the table. In an index cluster, the query for range of values will be able to make use of the cluster key index to find these rows. In a hash cluster, this query would result in a full table scan unless you had an index on the key column. Only exact equality searches (including in lists and subqueries) may be made on the hash key without using an index that supports range scans.

— When you create a hash cluster table, you must determine in advance, the number of hash keys your table will ever have. The number of HASHKEYs in a hash cluster is a fixed size. You cannot change the size of the hash table without a rebuild of the cluster. This does not in any way limit the amount of data you can store in this cluster; it simply limits the number of unique hash keys that can be generated for this cluster. That may affect performance due to unintended hash collisions if the value was set too low. Getting the size of the HASHKEYs and SIZE parameters right is crucial to avoid a rebuild.

— With a hash cluster, the tables will start out big and will take longer
to create, as Oracle must initialize each block, an action that normally takes
place as data is added to the table. They have the potential to have data in
their first block and their last block, with nothing in between. Full scanning
a virtually empty hash cluster will take as long as full scanning a full hash cluster.

• The hash cluster is allocated right from the beginning. Oracle will take
your HASHKEYS/ trunc(blocksize/SIZE) and allocate and format that space right away. As soon as the first table is put in that cluster, any full scan will hit every allocated block. This is different from every other table in this respect.

• Updates to hash cluster tables do not introduce significant overhead,
unless you update the HASHKEY, which would not be a good idea, as it would
cause the row to migrate

. Hash clusters allocate all the storage for all the hash buckets when the cluster is created, so they may waste space.. Full scans on single table hash clusters will cost as much as they would in a heap table.